AI Platform Engineer

AI Platform Engineer

📍 Location: New York, United States

🏢 Industry: Financial services

💼 Work Setting: Hybrid

Are you a senior platform engineering leader passionate about cloud-native architecture, AI infrastructure, platform reliability, and enterprise-scale AI enablement?

We are seeking a Principal AI Platform Architect (Staff-Level Individual Contributor) to define and drive the technical vision for a modern enterprise AI platform. This role provides architectural leadership across AI infrastructure, model serving, platform reliability, cloud engineering, governance, and developer experience without direct people management responsibilities.

The ideal candidate combines deep expertise in Kubernetes, cloud infrastructure, platform engineering, AI/ML systems, and large-scale distributed architectures with the ability to influence engineering organizations through technical leadership and strategic execution.

Key Responsibilities

AI Platform Architecture & Strategy

• Define technical architecture and long-term roadmap for enterprise AI platforms.
• Establish architectural standards and engineering principles for AI infrastructure.
• Drive strategic decisions related to:
• AI Platform Services
• Cloud Infrastructure
• Model Serving
• Platform Scalability
• Reliability Engineering
• Developer Experience
• Align platform capabilities with enterprise AI initiatives and business priorities.

Technical Leadership & Engineering Excellence

• Serve as the senior technical authority for platform engineering decisions.
• Lead architecture reviews and design discussions.
• Provide technical guidance and mentorship across engineering teams.
• Conduct deep technical reviews of designs, implementations, and platform services.
• Drive consistency in engineering standards and best practices.

AI Infrastructure & Model Serving

• Design and oversee enterprise AI infrastructure supporting:
• Large Language Models (LLMs)
• AI Inference Platforms
• Model Serving Systems
• Multi-Tenant AI Workloads
• GPU-Based Computing Environments
• Lead architecture for:
• LLM Gateways
• AI Service Layers
• Inference Pipelines
• Enterprise AI Integration Patterns
• Optimize platform performance and scalability for AI workloads.

Cloud & Kubernetes Engineering

• Architect cloud-native solutions across:
• AWS
• Azure
• Google Cloud Platform (GCP)
• Lead large-scale Kubernetes platform design and operations.
• Establish standards for:
• Containerized Platforms
• Multi-Tenant Environments
• Identity Federation
• Networking Architecture
• Cloud Security
• Ensure infrastructure remains secure, scalable, and resilient.

Platform Reliability & Operational Excellence

• Define and implement platform reliability strategy.
• Establish:
• Service Level Objectives (SLOs)
• Service Level Indicators (SLIs)
• Availability Standards
• Incident Management Processes
• Lead post-incident reviews and operational improvement initiatives.
• Drive observability, monitoring, and platform maturity.
• Continuously improve platform stability and performance.

Governance, Security & Compliance

• Design and implement enterprise controls related to:
• Data Residency
• Access Management
• Audit Logging
• Regulatory Compliance
• AI Governance
• Responsible AI Usage
• Ensure platform capabilities align with internal and external compliance frameworks.
• Embed secure-by-design principles across AI platform services.

Infrastructure as Code & GitOps

• Standardize cloud provisioning and deployment practices through:
• Terraform
• Pulumi
• ArgoCD
• GitOps Methodologies
• Develop reusable deployment patterns and platform automation frameworks.
• Reduce operational complexity through automation and standardization.
• Support scalable infrastructure management across engineering teams.

Internal Developer Platform (IDP) Leadership

• Drive development and evolution of internal developer platforms.
• Create self-service capabilities that improve engineering productivity.
• Enhance developer experience across AI and software engineering communities.
• Build platform capabilities that accelerate product delivery and innovation.

Cross-Functional Collaboration

• Partner closely with:
• AI Engineering Teams
• Product Organizations
• Cloud Engineering Teams
• Security Teams
• Enterprise Architecture Groups
• Communicate technical trade-offs and architectural decisions clearly.
• Influence strategic technology direction across the organization.
• Represent plat…